Transcript Slide 1

Census Micro Data
A Discussion
Prof. Ben Kiregyera
Director
African Centre for Statistics
August 2007
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COVERAGE
COVERAGE
I. Value of data and information
II. Issues arising from presentations
III.Conclusion
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I.
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VALUE OF DATA AND INFORMATION
data and information now universally
recognized as:
o part of the enabling environment for
development
o a priority for results-based agenda
(PRSPs, MDGs, etc) (e.g. Marrakech
Roundtable, 2004)
data and information have no intrinsic value
– they are not gold or silver. They have
extrinsic value which lies in their power to
inform processes e.g. policy debate &
design, planning, monitoring, etc.
their value lies in fact that:
o they can reach those who need them,
o can be easily understood
o are usable and actually used
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LIS-based research has catalyzed
changes in national policies
(LIS paper)
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DATA CYCLE
Planning
Analysis/Interpretation
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More and more data
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Need information from this
these data
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Policy-related information
information
Policy-related Analysis
Basic Analysis
Policy/
decisionmaker
Tables
Raw Data
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Data, Information, Knowledge, Actions
Informed Actions/ decisions
Knowledge
Value
addition
Information
Data
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Who should do data analysis?
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Preliminary or general analysis
 statisticians/data producers (NSO)
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Definitive or in-depth or detailed analysis
 subject-matter specialists
 researchers
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Importance of involving subject-matter specialists and
researchers in analysis
 enriches analysis by adding subject-matter
perspectives
 possibility to link policy variables to micro-level
outcomes (paper on LIS)
 enhances collaboration (advancing from
coordination to collaboration)
 spreads ownership of statistical products
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 feedback and advocacy
Basic principle of data analysis
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Data Collection
Feedback
Many times
Data Analysis
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NSO
Policy analysts
Researchers
Students
etc.
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II.
ISSUES ARISING FROM PRESENTATIONS
All presentations make a case for enhancing data management
including:
Country level – we see great need for:
 data archiving (IPUMS-International)
 creation of user-friendly and accessible
databases (documentation crucial - metadata) –
Benin’s “Jupiter”
 ensuring that databases are not empty boxes or
have “garbage”
 encouraging researchers to do more detailed data
analysis (Benin example shows need for this)
 a lot of value in doing broad range of analysis
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(through space and time)
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ISSUES ARISING FROM PRESENTATIONS (ctd)
Challenges:
i) appreciation of value of data (by data producers and users)
Users: use data for evidence-based policy (debate, design)
& decision-making; invest more to build statistical capacity &
development
Producers: ensure data quality & relevance; better data
management
ii) inconsistencies through time caused by changes in
definitions(1992 & 2002 Benin censuses)
- special attention to harmonization to permit comparability
ii) technical capacity (Benin paper – mutually beneficial TA)
iii) Statistics Acts which are not congenial
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Other laws (e.g. designating areas as rural or urban)
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International level – we see increasingly:
 construction of cross-national micro databases to
enhance research infrastructure
• Integrated European Census Microdata (IECM)
• Luxembourg Income Study (LIS)
• Redatam Software for micro data dissemination
& analysis
• IPUMS-International initiative – archiving,
integration and disseminate high-density census
micro data samples
 defining features of these databases include:
• research centres not only involved in data
analysis but also in “coordination, dissemination
and harmonization activities” (IECM)
• interest and cooperation of NSOs
• emphasis on integration & documentation
- IECM major part of project
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- IPUMS – International (post-harmonization)13
Creating databases become a driver
for data harmonization and
integration
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Challenges
 reliability and comparability of data sources across
countries
 lack of consistency, terminology, classifications,
question numbers and wording (all papers)
 confidentiality (strict conditions set by countries & more)
 ownership (IPUMS - International)
 dissemination
• Redatam developed by CELADE, Popn. Division
of ECLAS (UN) allows on-line processing of any
database over Internet
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• LIS uses remote-access system (primary means
to access data)
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• IPUMS posts census documents on Internet, etc
Other issues
 improved analytical capacity at NSOs
 training institutions should strike a productive
balance between “data demand” and “data
supply” in training programmes
 bigger dose of data analysis in training centres
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III.
CONCLUSION
Case made by all papers about need to add value to data
through more detailed analysis
Papers urge NSOs to move away from “risk avoidance” to
“risk management” (European statisticians)
Enhance research infrastructure by creating user-friendly
databases including micro databases
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Issues to address include integration, harmonization,
confidentiality
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Thank You
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